Cardiorenal ketone metabolism in healthy humans assessed by 11C-acetoacetate PET: effect of D-β-hydroxybutyrate, a meal, and age
Bibliographic record
Abstract
The heart and kidney have a high energy requirement, but relatively little is known about their utilization of ketones as a potential energy source. We assessed the metabolism of the ketone tracer, carbon-11 acetoacetate (11C-AcAc), by the left and right ventricles of the heart and by the kidney using positron emission tomography (PET) in n = 10 healthy adults under four experimental conditions: a 4-h fast (fasted) ± a single 12 g oral dose of D-beta-hydroxybutyrate (D-BHB), and a single complete, liquid replacement meal (hereafter referred to as the “fed” condition) ± a single 12 g oral dose of D-BHB. Under these experimental conditions, the kinetics of 11C-AcAc metabolism fitted a two-compartment model in the heart and a three-compartment model in the kidney. Plasma ketones were about 10-fold higher with the oral dose of D-BHB. During the four conditions, tracer kinetics were broadly similar in the myocardium and kidney cortex. 11C-AcAc metabolism by the kidney pelvis was similar in three of the four study conditions but, later, peaked significantly higher than that in the cortex; the exception was that the tracer uptake was significantly lower in the fed condition without D-BHB. 11C-AcAc uptake was significantly inversely correlated with age in the kidney cortex, and its oxidative metabolism was significantly positively correlated with age in the left ventricle. D-BHB blunted the insulin, gastric inhibitory peptide, and C-peptide response to the meal. This PET methodology and these acute metabolic perturbations would be suitable for future studies assessing cardiorenal ketone metabolism in conditions in which heart and kidney functions are experimentally modified or compromised by disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".